class_docstr: Tests gradients of univariate unidimensional functions.
docstr: Tests exp function.
docstr_tok: ["Tests","exp","function","."]
code: def test_exp(self, tol):
      """Tests exp function."""
      x_vals = np.linspace(-10, 10, 16, endpoint=False)
      func = lambda x: np.exp(x / 10.0) / 10.0
      g = qml.grad(func, 0)
      auto_grad = [g(x) for x in x_vals]
      correct_grad = np.exp(x_vals / 10.0) / 100.0
  
      assert np.allclose(auto_grad, correct_grad, atol=tol, rtol=0)
  
imports: import autograd
  import pytest
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 2 for calling the TestGradientUnivar obj's underlying member method code with example usage: obj.test_exp(tol) without return types